Neuro-Informatics ePosters

We present a comprehensive dataset of neural activity, compiled from 11 neuroimaging experiments in the nematode worm C. elegans. These source datasets, while collected under different experimental protocols, all measure neural activity via changes in calcium fluorescence in labeled subsets of the hermaphrodite worm’s…

Recent studies have demonstrated that brain areas involved in motor control display common representations of latent trajectories for both stereotypical and generalizable dynamical cortical behavior. However, current research often focuses on analyzing single tasks and individual sessions, missing the opportunity to…

Understanding how neuronal populations interact to process information and generate behaviour is a central goal of neuroscience. This can be challenging due to the high dimensionality of the neuronal populations, the dense interactions between them and the unobserved factors that influence the dynamics. The neuronal…

Reliably identifying cell types is crucial for understanding neural systems (1). However, classifying the neurons recorded in large-scale population recordings into well-defined types remains a challenge. While some methods rely on genetic targeting or anatomy for classification, a functional approach used in sensory…

A growing number of neuroimaging tools are being developed to enable data analysis in a more tool-independent manner when analyzing three- and four-dimensional brain imaging data in various statistical settings. Ideally, such tools still offer user interfaces that are accessible to those with a basic understanding of…

Investigations of transcriptomic and neuroimaging data imply that the spatial patterning of the brain transcriptome follows broad spatial trends in the brain network architecture, which can be used to study the molecular mechanisms of functional connectivity. However, the sophisticated pre-processing and data fusion…

Accurate localization of EEG scalp electrodes is crucial for precisely estimating the underlying neuronal activity from observed electrical potential changes on the scalp. Various techniques for electrode localization have been proposed, categorized into direct measurements on the subject's head or indirect methods…

Joint exploration of behavior, genes and brain structure holds the promise to provide a better understanding of neural circuits than unimodal data analyses. Several consortia provide extensive data resources of different modalities. However, analyses of heteromodal data require the expertise of computer scientists for…

Processing of large amounts of miniscopic data often poses a time-keeping procedure, requiring user’s efforts for step-by-step launching of various procedures, including manual intervention and inspection of putative neural units. The aim of this NoRMCorre- and CaImAn-based full-Python pipeline is to optimize users'…

Mapping behavioral actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioral data increases, there is growing interest in modeling neural dynamics during adaptive behaviors to probe neural representations. In particular, neural latent embeddings can reveal…

Intracortical brain-computer interfaces (iBCIs) can restore voluntary movement to people with paralysis by translating their brain activity into a control signal for an external device. Maintaining stable iBCI performance is challenging due to instabilities at the neural interface, such as shifts in electrode position…

The availability of high-density electrophysiology is transforming systems neuroscience and enables virtually any experimental lab to simultaneously acquire activity from hundreds of neurons throughout the brain. However, extracting single-cell activity from the resulting large datasets remains a major challenge:…